Multiple structure alignment and consensus identification for proteins

TL;DR: An algorithm is presented to compute a multiple structure alignment for a set of proteins and to generate a consensus structure which captures common substructures present in the given proteins, and it works directly with the coordinate representation in three dimensions with no loss of spatial information.

Abstract: An algorithm is presented to compute a multiple structure alignment for a set of proteins and to generate a consensus structure which captures common substructures present in the given proteins. The algorithm is a heuristic in that it computes an approximation to the optimal alignment that minimizes the sum of the pairwise distances between the consensus and the transformed proteins. A distinguishing feature of the algorithm is that it works directly with the coordinate representation in three dimensions with no loss of spatial information, unlike some other multiple structure alignment algorithms that operate on sets of backbone vectors translated to the origin; hence, the algorithm is able to generate true alignments. Experimental studies on several protein datasets show that the algorithm is quite competitive with a well-known algorithm called CE-MC. A web-based tool has also been developed to facilitate remote access to the algorithm over the Internet.